class_docstr: Layer that can safely used in a tf.data pipeline.
  
  The `call()` method must solely rely on `self.backend` ops.
  
  Only supports a single input tensor argument.
code: def _get_seed_generator(self, backend=None):
      if backend is None or backend == keras.backend.backend():
          return self.generator
      if not hasattr(self, "_backend_generators"):
          self._backend_generators = {}
      if backend in self._backend_generators:
          return self._backend_generators[backend]
      seed_generator = SeedGenerator(self.seed, backend=self.backend)
      self._backend_generators[backend] = seed_generator
      return seed_generator
  
file_path: keras/keras/layers/preprocessing/tf_data_layer.py
imports: import tree
  import keras.backend
  from keras.layers.layer import Layer
  from keras.random.seed_generator import SeedGenerator
  from keras.utils import backend_utils
  from keras.utils import tracking
label_desc: Use image node_id 3 for calling the TFDataLayer obj's underlying member method code with example usage: obj._get_seed_generator(backend) and returns: seed_generator, self, self